{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/139422"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/139422","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"A Systems Approach to Effective AIOps Implementation","abstract":"Artificial Intelligence in IT Operations, or AIOps, has gained considerable attention and expectations over the past few years. However, implementing AIOps in organizations is challenging. This research aims to guide effective enterprise-level AIOps implementation by building a general framework using systems thinking methodologies. The framework proposed builds a structure on the rubric of socio aspect, technical aspect, socio-technical intersection, system dynamics, and environmental factors of AIOps implementation. Each aspect has its corresponding methodology from systems thinking theory. This research is beneficial and critical to organizations wanting to implement or in the process of implementing AIOps. First, this research helps to outline the whole problem space, including both socio and technical aspects. Second, it proposes a comprehensive framework that can be used as a reference for guiding AIOps implementation in real-world scenarios. Based on the actual situation of each organization, companies can build their own AIOps reference models using this framework. The framework bridges gaps between various teams, enabling effective cross-disciplinary collaboration. The framework also provides a big picture and a way to think holistically to all AIOps-related stakeholders and keep their expectations aligned. Moreover, with the systems thinking methodologies embedded in the framework, organizations can guide effective planning, communication, and risk management throughout the AIOps implementation process.","abstract_html":"Artificial Intelligence in IT Operations, or AIOps, has gained considerable attention and expectations over the past few years. However, implementing AIOps in organizations is challenging. This research aims to guide effective enterprise-level AIOps implementation by building a general framework using systems thinking methodologies. The framework proposed builds a structure on the rubric of socio aspect, technical aspect, socio-technical intersection, system dynamics, and environmental factors of AIOps implementation. Each aspect has its corresponding methodology from systems thinking theory. This research is beneficial and critical to organizations wanting to implement or in the process of implementing AIOps. First, this research helps to outline the whole problem space, including both socio and technical aspects. Second, it proposes a comprehensive framework that can be used as a reference for guiding AIOps implementation in real-world scenarios. Based on the actual situation of each organization, companies can build their own AIOps reference models using this framework. The framework bridges gaps between various teams, enabling effective cross-disciplinary collaboration. The framework also provides a big picture and a way to think holistically to all AIOps-related stakeholders and keep their expectations aligned. Moreover, with the systems thinking methodologies embedded in the framework, organizations can guide effective planning, communication, and risk management throughout the AIOps implementation process.","abstract_has_math":false,"creators":["Hua, Yunke"],"institution":"Massachusetts Institute of Technology","degree_name":"Master","degree_level":null,"degree_discipline":null,"degree_department":"System Design and Management Program.","school":null,"contributors":[],"advisors":["Rhodes, Donna H."],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-06","date_published":"2021-06","updated_at":"2026-07-22T22:20:50Z","subjects":[],"languages":[],"rights":["In Copyright - Educational Use Permitted","Copyright retained by author(s)"],"rights_urls":["https://rightsstatements.org/page/InC-EDU/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1721.1/139422","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Rhodes, Donna H."]},{"key":"dc:contributor.department","label":"Department","values":["System Design and Management Program."]},{"key":"dc:creator","label":"Author","values":["Hua, Yunke"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2022-01-14T15:10:33Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2022-01-14T15:10:33Z"]},{"key":"dc:date.issued","label":"Date","values":["2021-06"]},{"key":"dc:publisher","label":"Institution","values":["Massachusetts Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master","Master of Science in Engineering and Management"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright - Educational Use Permitted","Copyright retained by author(s)"]},{"key":"dc:rights.uri","label":"Rights URI","values":["https://rightsstatements.org/page/InC-EDU/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/1721.1/139422"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Artificial Intelligence in IT Operations, or AIOps, has gained considerable attention and expectations over the past few years. However, implementing AIOps in organizations is challenging. This research aims to guide effective enterprise-level AIOps implementation by building a general framework using systems thinking methodologies. The framework proposed builds a structure on the rubric of socio aspect, technical aspect, socio-technical intersection, system dynamics, and environmental factors of AIOps implementation. Each aspect has its corresponding methodology from systems thinking theory. This research is beneficial and critical to organizations wanting to implement or in the process of implementing AIOps. First, this research helps to outline the whole problem space, including both socio and technical aspects. Second, it proposes a comprehensive framework that can be used as a reference for guiding AIOps implementation in real-world scenarios. Based on the actual situation of each organization, companies can build their own AIOps reference models using this framework. The framework bridges gaps between various teams, enabling effective cross-disciplinary collaboration. The framework also provides a big picture and a way to think holistically to all AIOps-related stakeholders and keep their expectations aligned. Moreover, with the systems thinking methodologies embedded in the framework, organizations can guide effective planning, communication, and risk management throughout the AIOps implementation process."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M."]},{"key":"dc:title","label":"Title","values":["A Systems Approach to Effective AIOps Implementation"]}]}],"canonical_facts":{"dc:contributor.advisor":["Rhodes, Donna H."],"dc:contributor.department":["System Design and Management Program."],"dc:creator":["Hua, Yunke"],"dc:date.accessioned":["2022-01-14T15:10:33Z"],"dc:date.available":["2022-01-14T15:10:33Z"],"dc:date.issued":["2021-06"],"dc:description.abstract":["Artificial Intelligence in IT Operations, or AIOps, has gained considerable attention and expectations over the past few years. However, implementing AIOps in organizations is challenging. This research aims to guide effective enterprise-level AIOps implementation by building a general framework using systems thinking methodologies. The framework proposed builds a structure on the rubric of socio aspect, technical aspect, socio-technical intersection, system dynamics, and environmental factors of AIOps implementation. Each aspect has its corresponding methodology from systems thinking theory. This research is beneficial and critical to organizations wanting to implement or in the process of implementing AIOps. First, this research helps to outline the whole problem space, including both socio and technical aspects. Second, it proposes a comprehensive framework that can be used as a reference for guiding AIOps implementation in real-world scenarios. Based on the actual situation of each organization, companies can build their own AIOps reference models using this framework. The framework bridges gaps between various teams, enabling effective cross-disciplinary collaboration. The framework also provides a big picture and a way to think holistically to all AIOps-related stakeholders and keep their expectations aligned. Moreover, with the systems thinking methodologies embedded in the framework, organizations can guide effective planning, communication, and risk management throughout the AIOps implementation process."],"dc:description.degree":["S.M."],"dc:identifier.uri":["https://hdl.handle.net/1721.1/139422"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["In Copyright - Educational Use Permitted","Copyright retained by author(s)"],"dc:rights.uri":["https://rightsstatements.org/page/InC-EDU/1.0/"],"dc:title":["A Systems Approach to Effective AIOps Implementation"],"dc:type":["Thesis"],"thesis:degree_name":["Master","Master of Science in Engineering and Management"]},"updated_at":"2026-07-22T22:20:50Z"}